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Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind. | Tweet: @simmy_hanley @Schrise also a #delight
This tweet contains emotions: | joy, love, optimism |
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind. | Tweet: @jaybusbee Well, not Archie. No offense but he's kinda old.
This tweet contains emotions: | anger |
Task: Determine the degree of intensity for emotion E in the tweet, giving it a score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: Gas prices are hilarious. Cause they're simultaneously super subsidised and taxed
Emotion: joy
Intensity score: | 0.220 |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @_jesskardashian @trevschan2 both are awesome. People are missing out not watching fear!!!
Emotion: joy
Intensity class: | 1: low amount of joy can be inferred |
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: @SMalloy_LWOS that's not easy to blow up the LT on a run play. He created the seam for Sua to burst through
This tweet contains emotions: | joy |
Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state. | Tweet: It's now September and we're still battling a situation that was said to be handled March of this year. @ATT this is unacceptable
This tweet contains emotions: | anger, disgust, sadness |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @AnthonyEinzig I'm so sorry. This is heartbreaking and so scary. If it can happen there it can happen anywhere. Please be safe 🙏🏻 #terror
Emotion: fear
Intensity class: | 3: high amount of fear can be inferred |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: Afridi !!! 100 off 42 !! #mad
Emotion: anger
Intensity score: | 0.710 |
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Yo,if you're talking about horoscopes do you really have any clue as to what you're saying or are you gonna act offended when I question it?
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
Task: Quantify the sentiment intensity or valence level of the tweet, giving it a score between 0 (highly negative) and 1 (highly positive). | Tweet: Benefit out exhilaration called online backing off: JkUVmvQXY
Intensity score: | 0.621 |
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity. | Tweet: smiling but we're close to tears
Emotion: sadness
Intensity score: | 0.732 |
Task: Evaluate the valence intensity of the tweeter's mental state based on the tweet, assigning it a real-valued score from 0 (most negative) to 1 (most positive). | Tweet: It's so breezy I love it 🌬️🍃💛
Intensity score: | 0.806 |
Task: Quantify the intensity of emotion E in the tweet on a scale of 0 (least E) to 1 (most E). | Tweet: @vkon1 @WindyCOYS by all accounts he was poor first half. Started showboating once game was safe
Emotion: fear
Intensity score: | 0.148 |
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity. | Tweet: That's the old me though #imachildofgod #whatistwerking #sober #married #bye
Emotion: sadness
Intensity score: | 0.458 |
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind. | Tweet: Life's too short to be frowning for so long
This tweet contains emotions: | anger, optimism, sadness |
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: i've been rooting for him since the beginning #BB18
This tweet contains emotions: | anticipation, love, trust |
Task: Classify the tweet into one of seven ordinal categories, indicating the intensity of positive or negative sentiment expressed by the tweeter and reflecting their current mental state. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Wine drunk is the worst version of myself ffs, don't even remember seeing basshunter
Intensity class: | -3: very negative emotional state can be inferred |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: @chelseanews4you Best of luck blues army make us feeling goofy this season again BLUES TILL ETERNITY
Emotion: sadness
Intensity score: | 0.327 |
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity. | Tweet: The Sorrow is grim reminder of how bad I can be at video games and how I could get a bit too trigger happy at times. RIP #MGS3
Emotion: sadness
Intensity score: | 0.604 |
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: Fingers crossed I can finish all my work early enough this Friday in time to catch @Raury at LIB 😦 #timetogrind
This tweet contains emotions: | anticipation, joy, optimism |
Task: Gauge the level of intensity for emotion E in the tweet, assigning it a score between 0 and 1. A score of 0 indicates the lowest intensity, while a score of 1 indicates the highest intensity. | Tweet: [ @TheChicMystique ] — hurting badly and that he can't just leave him like that. Angry and heartless. ]\n\nI promise you that I'll be back, —
Emotion: fear
Intensity score: | 0.545 |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: In other news. My legs hurt. #running #5kin26mins #dreadful #flatfeet
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Round 2 #panic #pcola
Emotion: fear
Intensity class: | 1: low amount of fear can be inferred |
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: I can not depict what I feel right now.. I feel jubilant yet anxious, or..dunno. It seems like now I'm having something worth wait everyday.
This tweet contains emotions: | fear, joy, sadness |
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: @iamglenn35 the forth character? No... not gleeful enough...
This tweet contains emotions: | anticipation, disgust, sadness |
Task: Gauge the intensity of sentiment or valence in the tweet, indicating a numerical value between 0 (extremely negative) and 1 (extremely positive). | Tweet: United Airline at Newark needs more Kiosks so that people won't miss their cut off time. And hire more ppl too. #horrible
Intensity score: | 0.179 |
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: @reikimuse @MHChat I am beyond the sadness point. Have done it inside out. I live with CPTSD and BPD I can't always do the pity party
Emotion: sadness
Intensity score: | 0.792 |
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @RadioX @ChrisMoyles wow. not heard this in forever. Random but. great #xph
Emotion: anger
Intensity class: | 0: no anger can be inferred |
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Brighten up a gloomy day with a @SiennaXOfficial spray tan, we have a tan to suit everybody! #spraytan #tan #summer #godalming #hurtmore
Emotion: anger
Intensity class: | 0: no anger can be inferred |
Task: Assign one of four ordinal intensity classes of emotion E to a given tweet based on the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: [ @TheChicMystique ] — hurting badly and that he can't just leave him like that. Angry and heartless. ]\n\nI promise you that I'll be back, —
Emotion: anger
Intensity class: | 2: moderate amount of anger can be inferred |
Task: Evaluate the valence intensity of the tweeter's mental state based on the tweet, assigning it a real-valued score from 0 (most negative) to 1 (most positive). | Tweet: Happy Amazon Prime day to all my primers 😆
Intensity score: | 0.629 |
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: How shit and depressing is this weather wish I can travel the world for a living
Emotion: fear
Intensity score: | 0.718 |
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: the thing with Twitter is i only remember to tweet when i'm bored or alone and then it comes across like i have a really dull and sad life.👽
This tweet contains emotions: | pessimism, sadness |
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind. | Tweet: @Ashleyavitia_ don't leave me
This tweet contains emotions: | fear, sadness |
Task: Determine the degree of intensity for emotion E in the tweet, giving it a score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: @omgitsbrittanyy @WittLowry u probably irritate the shit out of him always talking to him. He could probably give 2 shits about u lol 🖕🏻
Emotion: anger
Intensity score: | 0.667 |
Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: I'm a shy person
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Assign a numerical value between 0 (least E) and 1 (most E) to represent the intensity of emotion E expressed in the tweet. | Tweet: @doubtcaspar babe :(( remember I'm ALWAYS here if u need a little cheering up or talk, ily lots💘
Emotion: joy
Intensity score: | 0.417 |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: I freaking hate working with #word on my phone #write #writing #writerslife #writerproblems #writer
Emotion: anger
Intensity score: | 0.542 |
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind. | Tweet: American horror story and chill tonight?😌
This tweet contains emotions: | fear |
Task: Determine the appropriate ordinal classification for the tweet, reflecting the tweeter's mental state based on the magnitude of positive and negative sentiment intensity conveyed. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Does anyone remember a movie that is animated in the late 70's called Shame of the Jungle John Bulushi was in it wild if that's your taste
Intensity class: | 0: neutral or mixed emotional state can be inferred |
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: On the last episode of #MakingAMurderer poor Brendan glad they #appeal it #shocking #crime #documentary #reallife
This tweet contains emotions: | surprise |
Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Freakin a...I deleted half the episode of BIP on accident #bachelorinparadise
Intensity class: | -2: moderately negative emotional state can be inferred |
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: So my Indian Uber driver just called someone the N word. If I wasn't in a moving vehicle I'd have jumped out #disgusted
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: By the way...in case you didnt know...joshuas goin out tonight...to take the trash out and then play blues at ever us 6.75
Emotion: sadness
Intensity score: | 0.319 |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: ' i can't even tell u a lie I felt like u were special, till I realized wassup and left, got u feeling dreadful '
Emotion: fear
Intensity score: | 0.603 |
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: i feel furious
This tweet contains emotions: | anger, disgust |
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity. | Tweet: @icapturpix @DRUDGE_REPORT I agree. This current, ultra-left Democratic party lost a lot of members, including myself. I switched to Repub.
Emotion: sadness
Intensity score: | 0.333 |
Task: Place the tweet into a specific intensity class, reflecting the intensity of the mentioned emotion E and the user's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Just got back from seeing @GaryDelaney in Burslem. AMAZING!! Face still hurts from laughing so much #hilarious
Emotion: joy
Intensity class: | 3: high amount of joy can be inferred |
Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state. | Tweet: @ArcadianLuthier -- taking out his feelings on Kei unfairly. His lips form a frown as he tries to walk away.
This tweet contains emotions: | anger, disgust, sadness |
Task: Determine the appropriate intensity category of emotion E for the tweet, reflecting the emotional state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @rachelkennedy84 @callummay @Ned_Donovan @JeyyLowe @jimwaterson @dats Can it do the bell ringing and incense at consecration?
Emotion: anger
Intensity class: | 0: no anger can be inferred |
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind. | Tweet: @serendipity127_ @zombiecalorie @Angel_Eyes66 I'm sensing a theme here tho lol #angry
This tweet contains emotions: | anger, disgust, sadness |
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state. | Tweet: @WhiteJennyB @EmreUslu jenny white u r the dumbest here .. What r u trying ? Get lost..
This tweet contains emotions: | anger, disgust |
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: @cherrivarisco @audubonsociety Oh yes, males are colourful and the Females are dull, so that they can blend in to their environment.
Emotion: sadness
Intensity score: | 0.292 |
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive). | Tweet: MC: what are you listen to these days?\nBogum: these days I feel gloomy, I listen to ccm (spiritual song) often.\n\nChurch oppa mode. :)
Intensity score: | 0.422 |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: #ContentwiththeLordsPortion:O satisfy us early with thy #mercy;that we may #rejoice & be glad all our days.#Ps 90:14 #gladness #joy #delight
Emotion: joy
Intensity class: | 3: high amount of joy can be inferred |
Task: Assess the intensity of sentiment or valence in the tweet, representing the tweeter's mental state with a real-valued score between 0 (extremely negative) and 1 (extremely positive). | Tweet: We have been a better second half team this season. So there's that.
Intensity score: | 0.550 |
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state. | Tweet: 'We can throw stones, complain about them, stumble on them, climb over them, or build with them.' — William Arthur Ward. #inspiring
This tweet contains emotions: | joy, optimism |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: Everything I see of American police training seems calculated to trample human dignity, inflame outrage, and escalate confrontations.
Emotion: anger
Intensity score: | 0.604 |
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: Whatever you decide to do make sure it makes you #happy.
This tweet contains emotions: | joy, love, optimism |
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state. | Tweet: I can't WAIT to go to work tomorrow with a high as fuck fever. [sarcasm]\nHopefully I'll feel better tomorrow.\nBut I doubt it. #pessimism
This tweet contains emotions: | pessimism, sadness |
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity. | Tweet: @devbostick @daniel_henshall Where is it? :O because it's so beautiful
Emotion: joy
Intensity score: | 0.661 |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Whatt a trailerrrr !!! @karanjohar @AnushkaSharma #RanbirKapoor #AishwaryaRaiBachchan i am COMPLETELY BLOWN !! #awestruck #longingformore
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: Home is where the heart lies ! Love my little island but my birth city just ain't acting right & im not feeling too good about it
This tweet contains emotions: | disgust, sadness |
Task: Rate the intensity of emotion E in the tweet on a scale of 0 to 1, with 0 indicating the least intensity and 1 indicating the highest intensity. | Tweet: smiling through the stress :) :) :) :) :) :) :( :( :( :( :( :( :(
Emotion: joy
Intensity score: | 0.280 |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @WHUFC_HUB @westhamtransfer @TheHammers_ I don't see any reason for optimism at this point. Just stringing together bad performances.
Emotion: joy
Intensity class: | 0: no joy can be inferred |
Task: Estimate the strength of emotion E in the tweet by assigning it a real-valued score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: @MrHenvin Thank you, happy birthday to you as well!
Emotion: joy
Intensity score: | 0.812 |
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: @kjwinston11 2. the N-word. But I think all Afr-Am are entitled to it: we shouldn't take away from them the insult they have claimed back.
This tweet contains emotions: | anger, disgust, sadness |
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: I'm literally never home and my parents threaten to charge rent if I don't start cleaning the house everyday. OK.
This tweet contains emotions: | fear |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: i have so much hw tonight im offended
This tweet contains emotions: | anger, disgust |
Task: Identify the primary emotion conveyed in the tweet and assign it to either 'neutral or no emotion' or one or more of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best capture the tweeter's mental state. | Tweet: When a guy comes on the train that smells like a mixture of a damp dog, old sweat and sewage works!!!! #gross #getoffthetrain #smelly
This tweet contains emotions: | anger, disgust, joy |
Task: Assess the magnitude of emotion E in the tweet using a real number between 0 and 1, where 0 denotes the least intensity and 1 denotes the most intensity. | Tweet: I've got some new pens to break in. Name an animated series and I'll draw you in that style 🖍
Emotion: joy
Intensity score: | 0.480 |
Task: Evaluate the tweet for emotional cues and classify it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that indicate the tweeter's state of mind. | Tweet: Came in to work today 1.5 hours late.1st thing I hear: 'Ma'am,the big boss has been waiting for you in his office.' #panic #hateBeingLate 😩😪
This tweet contains emotions: | fear, sadness |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @MJPWGaming exactly not some flaming reject from fast and furious
Emotion: anger
Intensity class: | 1: low amount of anger can be inferred |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: Niggas murking in each other. In murky water, I try to swim.
This tweet contains emotions: | anger, disgust, optimism |
Task: Calculate the intensity of emotion E in the tweet as a decimal value ranging from 0 to 1, with 0 representing the lowest intensity and 1 representing the highest intensity. | Tweet: also i had an awful nightmare involving being sick where worms were involved i was so disgusted when i woke up
Emotion: fear
Intensity score: | 0.896 |
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state. | Tweet: *in the car with mariah, the bass is literally shaking the windows, hard rap blasting, no one is talking, looking straight ahead*
This tweet contains emotions: | |
Task: Assess the emotional content of the tweet and classify it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that best represent the tweeter's mental state. | Tweet: @ctp It's daunting trying to follow Swift news/trends, and facing mind-shattering patterns/terms left and right. I'm trying to adopt gently.
This tweet contains emotions: | anticipation, optimism, trust |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @1720maryknoll I was #fuming Kenny.
Emotion: anger
Intensity class: | 2: moderate amount of anger can be inferred |
Task: Classify the tweet into one of four ordinal intensity levels, indicating the degree of emotion E experienced by the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Good luck to all Fury-Haney players playing this weekend at the Future Stars showcase in Frisco, Tx. #KGB #G-town #fury
Emotion: anger
Intensity class: | 1: low amount of anger can be inferred |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @lakeline I still find you pleasing.
Emotion: joy
Intensity class: | 1: low amount of joy can be inferred |
Task: Analyze the tweet's sentiment and assign it to either 'neutral or no emotion' or one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: Condolences to the JC and the Georges family..
This tweet contains emotions: | pessimism, sadness |
Task: Determine the degree of intensity for emotion E in the tweet, giving it a score between 0 and 1, where 0 signifies the least intensity and 1 signifies the greatest intensity. | Tweet: Watch this amazing live.ly broadcast by @its.finfin #musically
Emotion: joy
Intensity score: | 0.458 |
Task: Determine the appropriate intensity class for the tweet, reflecting the level of emotion E experienced by the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @Lillie_Billy don't worry me and my mans @JJB1Owens gave him a piece of our mind
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Classify the tweet into one of seven ordinal categories, indicating the intensity of positive or negative sentiment expressed by the tweeter and reflecting their current mental state. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: I love anxiety #sarcasm
Intensity class: | 0: neutral or mixed emotional state can be inferred |
Task: Place the tweet into an appropriate ordinal class, representing the tweeter's mental state by assessing the levels of positive and negative sentiment intensity conveyed. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: A 'non-permissive environment' is also called a 'battleground' - #MilSpeak #hilarious
Intensity class: | 1: slightly positive emotional state can be inferred |
Task: Place the tweet into a specific intensity class, reflecting the intensity of the mentioned emotion E and the user's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: It's so gloomy outside. I wish it was as cold as it looked
Emotion: sadness
Intensity class: | 2: moderate amount of sadness can be inferred |
Task: Categorize the tweet's emotional tone as either 'neutral or no emotion' or identify the presence of one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: Exciting day ahead...lunch @Panoramic34 with the girls #Foodie #yummy #myday #Friends
This tweet contains emotions: | anticipation, joy, optimism |
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @AnthonyEinzig I'm so sorry. This is heartbreaking and so scary. If it can happen there it can happen anywhere. Please be safe 🙏🏻
Emotion: fear
Intensity class: | 3: high amount of fear can be inferred |
Task: Classify the mental state of the tweeter based on the tweet, determining if it is 'neutral or no emotion' or characterized by any of the provided emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust). | Tweet: When you forget to mention you were bought dreamboys tickets 🙄😂
This tweet contains emotions: | joy, love, sadness |
Task: Classify the tweet's emotional intensity into one of four ordinal levels of emotion E, providing insights into the mental state of the user. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @isthataspider @dhodgs i will fight this guy! Don't insult the lions like that! But seriously they kinda are.Wasted some of the best players
Emotion: anger
Intensity class: | 3: high amount of anger can be inferred |
Task: Determine the prevailing emotional tone of the tweet, categorizing it as either 'neutral or no emotion' or as one or more of the given emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that most accurately represent the tweeter's mental state. | Tweet: Get to work and there's a fire drill. #fire #outthere #inthedark
This tweet contains emotions: | anger, disgust |
Task: Categorize the tweet based on the intensity of the specified emotion E, capturing the tweeter's mental state. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: Changing my hair again #shocking
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Classify the tweet into one of seven ordinal classes, corresponding to various levels of positive and negative sentiment intensity, that best represents the mental state of the tweeter. 3: very positive mental state can be inferred. 2: moderately positive mental state can be inferred. 1: slightly positive mental state can be inferred. 0: neutral or mixed mental state can be inferred. -1: slightly negative mental state can be inferred. -2: moderately negative mental state can be inferred. -3: very negative mental state can be inferred. | Tweet: Rec'd call 2day from Haitian church we started in Florida some 15yrs ago. Preparing to acquire their own bldg. Wanted me to know.
Intensity class: | 1: slightly positive emotional state can be inferred |
Task: Categorize the tweet into an intensity level of the specified emotion E, representing the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @ATTCares this really sucks how much your customer service sucks. I've been hung up on three times and this is absolutely horrible.
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Classify the tweet into one of four ordinal classes of intensity of emotion E that best represents the mental state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: @chelsysayshi @Adweek touché! I'll start paying more attention and test this 🕵🏻♀️ #AdweekChat
Emotion: fear
Intensity class: | 0: no fear can be inferred |
Task: Evaluate the strength of emotion E in the tweet, providing a real-valued score from 0 to 1. A score of 0 denotes the absence of the emotion, while a score of 1 indicates the highest degree of intensity. | Tweet: everything in the dream stayed there
Emotion: sadness
Intensity score: | 0.271 |
Task: Categorize the tweet's emotional expression, classifying it as either 'neutral or no emotion' or as one or more of the specified emotions (anger, anticipation, disgust, fear, joy, love, optimism, pessimism, sadness, surprise, trust) that reflect the tweeter's state of mind. | Tweet: i resent biting my tongue.
This tweet contains emotions: | anger, disgust |
Task: Assess the sentiment intensity or valence level of the tweet, ranging from 0 (extremely negative) to 1 (extremely positive). | Tweet: #ahs6 every 5 minutes I've been saying 'nope nope I'd be gone by now.' 'MOVE' or 'GTFO' so thank you for the
Intensity score: | 0.431 |
Task: Measure the level of emotion E in the tweet using a real-valued score between 0 and 1, where 0 represents the lowest intensity and 1 represents the highest intensity. | Tweet: @patienceinbee @camposanto But I decided to be a bit lackadaisical about getting dressed to get groceries.
Emotion: sadness
Intensity score: | 0.417 |
Task: Assign a suitable level of intensity of emotion E to the tweet, representing the emotional state of the tweeter. 0: no E can be inferred. 1: low amount of E can be inferred. 2: moderate amount of E can be inferred. 3: high amount of E can be inferred. | Tweet: If I had a little bit of extra money I would blow the whole paycheck and go to one of the two of @KygoMusic's concerts in LA. #serious
Emotion: sadness
Intensity class: | 0: no sadness can be inferred |
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Citation Information
Liu, Z., Yang, K., Xie, Q., Zhang, T., & Ananiadou, S. (2024, August). Emollms: A series of emotional large language models and annotation tools
for comprehensive affective analysis. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5487-5496).
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